Abstract: A method and system of maintaining electrical power to one or more designated loads connected to an electrical bus that is selectively connected to an electric power grid as a first source of power and to an inverter for providing power to the bus from a second source of electrical power. A controller receives an input indicating if the bus is connected to the grid. The inverter is operated to be synchronized with the grid and provide a selected amount of active and reactive electrical power from the second source of electrical power while the one or more designated loads receive electrical power from the grid. Connection of the bus to the grid is monitored and at the time the electrical bus is no longer receiving power from the grid, the inverter is operated to provide required power without interruption to the one or more designated loads of the bus.

Abstract: A spurious outlier detection-system is provided. The system includes a memory having computer-readable instructions stored therein and a processor configured to execute the computer-readable instructions to receive time-series data from one or more sensors and/or applications, process the time-series data to detect one or more change points based on a pre-defined cost function. The processor is configured to identify data chunks between the change points using pre-determined window sizes and to estimate smooth reconstructed values (SRVs) for each of the change point data chunks between two consecutive change points to identify one or more global outliers from the SRVs. The processor is configured to determine distribution of the global outliers using kernel density for each change point data chunk and identify one or more true outliers from the distribution of the global outliers based upon a skewness of the distribution.

Abstract: A spurious outlier detection-system is provided. The system includes a memory having computer-readable instructions stored therein and a processor configured to execute the computer-readable instructions to receive time-series data from one or more sensors and/or applications, process the time-series data to detect one or more change points based on a pre-defined cost function. The processor is configured to identify data chunks between the change points using pre-determined window sizes and to estimate smooth reconstructed values (SRVs) for each of the change point data chunks between two consecutive change points to identify one or more global outliers from the SRVs. The processor is configured to determine distribution of the global outliers using kernel density for each change point data chunk and identify one or more true outliers from the distribution of the global outliers based upon a skewness of the distribution.